Real estate data analysis and visualization are important contents of urban research and urban management, while big data and computer technology provide scientific methods and tools for them. This research is based on big data technology. Firstly, the paper obtains the relevant massive data on the network through computer technology, and makes a visual analysis of the current situation. Secondly, the paper uses Kriging interpolation method to predict and analyze the trend of house prices and display them visually. Finally, the paper establishes an ordinary least squares (OLS) regression model to visualize and quantify the location factors affecting house prices, and makes a spatial differentiation analysis.The research results of this paper explore the spatial pattern and action mechanism of house prices in Xi'an, which has a certain reference significance for optimizing urban spatial layout and rational allocation of urban resources. At the same time, this paper establishes a set of methods of big data mining, data analysis, data visualization and extracting factors affecting house prices based on computer technology, which provides an idea for the application of big data in real estate and urban planning and management.